• Journal of Communications and Networks
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• v.18 no.2
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• pp.210-217
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• 2016

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complexMIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.647-666
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• 2009

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1063-1071
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• 2008

This paper proposes a prior maximum likelihood (ML) detection verifier which has an ability to verify if the zero forcing (ZF) detection results are identical to the ML detection results. Since more than 90% of ZF detection results are identical to ML detection results, the proposed verifier makes it possible to omit the computationally complex ML detection in 90% cases of MIMO signal detections. The proposed verifier is designed by using the diversity gain obtained from converting MIMO signal into single input multiple output (SIMO) signals. In the proposed method, single input multiple output (SIMO) signals for each transmit antenna are separated from MIMO signals after the MIMO signals are detected by ZF method. Computer simulations show that the true alarm probability of the proposed verifier is more than 80% and the false alarm probability is less than $10^{-4}$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12A
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• pp.1198-1204
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• 2006

In this paper, we extend SVR-MMSE detection scheme which is proposed in MIMO system to MIMO-OFDM system, and evaluate performance of the system in frequency selective fading channel. First of all, we explain about typical MIMO-OFDM system and detection scheme of constant modulus signals in this system. And compare proposed SVR-MMSE with Zero Forcing, Minimum Mean Square Error which is conventional detection scheme. we identify that the performance of the proposed system is shown different by varying doppler frequency in frequency selective fading channel using jakes channel model. The result of detection performance by the proposed SVR-MMSE in this simulation, it shows that proposed algorithm have a good performance in MIMO-OFDM systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.413-423
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• 2014

With the increasing demands on high data rate, there has been growing interests in multi-input multi-output (MIMO) technology based on spatial multiplexing (SM) since it can transmit independent information in each spatial stream. Recent standards such as 3GPP LTE-advanced and IEEE 802.11ac support up to eight spatial streams, and massive MIMO and mm-wave systems that are expected to be included in beyond 4G systems are considering employment of tens to hundreds of antennas. Since the complexity of the optimum maximum likelihood based detection method increases exponentially with the number of antennas, low-complexity SM MIMO detection becomes more critical as the number of antenna increases. In this paper, we first review the results on the detection schemes for SM MIMO systems. In addition, massive MIMO reception schemes based on simple linear filtering which does not require exponential increment of complexity will be explained, followed by brief description on receiver design for future high dimensional SM MIMO systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.15-20
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• 2016

Compared to the MIMO system using the spatial multiplexing methods and the MIMO system using the diversity scheme achieved a high rate, but the lower the diversity gain to improve the data transmission reliability should separate the spatial stream at the MIMO receiver. In this paper, we compared Channel capacity detection methods with the Lattice code, the 3-user interference channel and linear channel interference detection methods ZF (Zero Forcing) and MMSE (Minimum Mean Square Error) detection methods. The channel is a Diagonal channel. In other words, Diagonal channel is confirmed by the inverse matrix satisfies the properties of Jacket are element-wise inverse to $[H]_N[H]_N^{-1}=[I]_N$.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.136-144
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• 1999

This paper deals with the fault detection problem in uncertain linear multivariable systems and its application. A robust fault detection method presented by Kim et a. (1998) for MIMO (Multi Input/Multi Output) systems has been adopted and applied to the twin rotor MIMO experimental setup using industrial DSP. The system identification problem is formulated for the twin rotor MIMO system and its parameters are estimated using experimental data. Based on the estimated parameters, some fault detection simulations are performed using the robust fault detection method, which shows that the preformance is satisfied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.535-544
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• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.447-450
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• 2009

In this paper, binary pulse-antipodal modulation (2PAM) direct-sequence (DS) ultra-wideband (UWB) system is applied to multiple input multiple output (MIMO) system using vertical bell lab layered space-time (V-BLAST) structure to achieve high-data-rate communications over indoor wireless channels. The relationship between antenna dimension and BER performance of 2PAM DS UWB MIMO system is discussed. In the receiver of UWB-MIMO system, various MIMO detection algorithms such as zero-forcing (ZF), ZF-ordered successive interference cancellation (OSIC), minimum-mean-square-error (MMSE), MMSE-OSIC and maximum likelihood (ML) are comparatively studied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.932-939
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• 2008

Recently lattice-reduction (LR) has been used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection. In this paper, we propose the Lattice-Reduction-aided scheme based on extended noise variance matrix to search good candidate symbol set in quantization step. Then this scheme estimates transmitted symbol with Semidefinite Relaxation by candidate symbol set. Simulation results in a random MIMO system show that the proposed scheme exhibits improved performance and a slight increase in complexity.